NickyNicky/Mistral-7B-OpenOrca-oasst_top1_2023-08-25-v3
NickyNicky/Mistral-7B-OpenOrca-oasst_top1_2023-08-25-v3 is a 7 billion parameter causal language model fine-tuned from Open-Orca/Mistral-7B-OpenOrca. This model leverages the OpenAssistant/oasst_top1_2023-08-25 dataset for instruction tuning and incorporates attention sink mechanisms for potentially improved long-context handling. It is designed for general-purpose conversational AI and instruction-following tasks, with a context length of 4096 tokens.
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Model Overview
NickyNicky/Mistral-7B-OpenOrca-oasst_top1_2023-08-25-v3 is a 7 billion parameter instruction-tuned language model built upon the Open-Orca/Mistral-7B-OpenOrca base model. It has been further fine-tuned using the OpenAssistant/oasst_top1_2023-08-25 dataset, which includes multilingual conversational data across 20 languages.
Key Features & Training Details
- Base Model: Fine-tuned from Open-Orca/Mistral-7B-OpenOrca.
- Instruction Tuning: Utilizes the OpenAssistant/oasst_top1_2023-08-25 dataset for enhanced instruction-following capabilities.
- Attention Sinks: Incorporates
attention_sinkstechnology, potentially improving performance and efficiency for longer contexts by managing attention mechanisms more effectively. This feature can be configured with parameters likeattention_sink_sizeandattention_sink_window_sizeduring inference. - Flash Attention: Training and inference can optionally leverage
flash-attentionfor speed optimizations, particularly on supported GPU hardware. - Context Length: Supports a maximum context length of 4096 tokens.
Intended Use Cases
This model is suitable for a variety of conversational AI and instruction-following applications, including:
- General Chatbots: Engaging in open-ended conversations.
- Question Answering: Providing informative responses to user queries.
- Content Generation: Assisting with text creation based on prompts.
- Multilingual Interaction: Benefiting from the diverse language coverage of its training dataset.